معرفی
Olaf Wiest serves as the Grace-Rupley Professor of Chemistry & Biochemistry at the University of Notre Dame's College of Science, holding office in McCourtney Hall. With continuous academic service since 1996—from Assistant Professor (1996-2001) to Associate Professor (2001-2005), Professor (2005-2024), and current endowed chair position—he maintains active research and teaching responsibilities.
His educational background includes a Dr. rer. nat. (1993) and Diplom (1991) from the University of Bonn, Germany, followed by postdoctoral work at UCLA (1993-1995). Key research interests span catalysis, computational chemistry, drug design for rare diseases (particularly Niemann-Pick Type C), epigenetic modulators targeting histone deacetylases, and machine learning applications in chemical reaction prediction. His interdisciplinary work bridges organic chemistry, biophysics, and artificial intelligence, frequently involving collaborations across synthetic chemistry, biology, physics, and medical research.
Wiest's publication trends reveal a strong focus on computational-experimental integration, with recent work emphasizing AI-driven chemistry (2023-2025), including transfer learning for reaction prediction, large language models for molecular analysis, and machine learning potentials for catalytic reactions. His group maintains dual expertise in traditional organic synthesis (catalysis, enzyme mechanisms) and cutting-edge computational methods (Q2MM, virtual screening).
- Research Achievement Award, University of Notre Dame (2025)
- Fellow, American Association for the Advancement of Science (2012)
- John Kaneb Award for undergraduate teaching (2004)
- Camille Dreyfus Teacher-Scholar Award (2001)
- NSF CAREER Award (1997)
- NIH First Award (1997)
His research group actively mentors graduate students in organic and biophysical chemistry projects, with significant grant support evidenced by NIH/NSF awards and industry collaborations. Current work includes developing computational tools for stereoselective catalysis (CatVS, Q2MM) and therapeutic strategies for rare diseases. The Wiest Lab operates at the intersection of experimental synthesis and computational modeling, utilizing advanced techniques like time-resolved crystallography and machine learning for reaction prediction.
